Methods, devices, and systems for impact detection and reporting for structure envelopes

ABSTRACT

A sensor system for a structure comprises a sensor node in force transmitting contact with an impact receiving surface of a structure envelope of the structure. The sensor node is configured to generate first sensor data associated with the structure envelope of the structure and perform a first set of operations to filter out unwanted data from the first sensor data to form a first filtered dataset. The sensor system includes a sensor hub in communication with the sensor node. The sensor hub is configured to receive the first filtered dataset from the sensor node and perform a second set of operations on the first filtered dataset to identify an event experienced by the structure envelope that caused the sensor node to produce the first sensor data.

CROSS REFERENCE TO RELATED APPLICATIONS

This application claims the benefit of U.S. Provisional Application No.63/141,756, filed on Jan. 26, 2021, which application is incorporatedherein by reference in its entirety.

FIELD

The disclosure relates generally to impact detection and reporting forstructure envelopes.

BACKGROUND

Insurance providers for real property, such as for residential andcommercial buildings, often rely upon the insured to report propertydamage and/or incidents that may have caused property damage, which maylead to delays in reporting, inaccurate reporting, fraudulent reporting,and/or other problems that introduce inefficiencies to the insuranceindustry.

SUMMARY

In an illustrative embodiment, a sensor system for a structure comprisesa sensor node in force transmitting contact with an impact receivingsurface of a structure envelope of the structure. The sensor node isconfigured to generate first sensor data associated with the structureenvelope of the structure and perform a first set of operations tofilter out unwanted data from the first sensor data to form a firstfiltered dataset. The sensor system includes a sensor hub incommunication with the sensor node. The sensor hub is configured toreceive the first filtered dataset from the sensor node and perform asecond set of operations on the first filtered dataset to identify anevent experienced by the structure envelope that caused the sensor nodeto produce the first sensor data.

In another illustrative embodiment, an impact detection method for astructure comprises producing, by an impact sensor of a first node of asensor system, first sensor data associated with a structure envelope ofthe structure. The impact sensor is in force-transmitting contact withan impact receiving surface of the structure envelope to detect impactsto the impact receiving surface. The method comprises performing, at thefirst node, a first set of operations to filter out unwanted data fromthe first sensor data to form a first filtered dataset, receiving, at asecond node of the sensor system, the first filtered dataset from thefirst node, and performing, at the second node, a second set ofoperations on the first filtered dataset to identify an eventexperienced by the structure envelope that caused the sensor to producethe first sensor data.

In another illustrative embodiment, a sensor system comprises a firstnode in force transmitting contact with an impact receiving surface of astructure envelope of the structure. The first node is configured togenerate first sensor data associated with the structure envelope of thestructure and perform a first set of operations to filter out unwanteddata from the first sensor data to form a first filtered dataset. Thesensor system comprises a second node in communication with the firstnode. The second node is configured to receive the first filtereddataset from the first node, and perform a second set of operations onthe first filtered dataset to identify an event experienced by thestructure envelope that caused the first node to produce the firstsensor data.

Any aspect in combination with any one or more other aspects.

Any one or more of the features disclosed herein.

Any one or more of the features as substantially disclosed herein.

Any one or more of the features as substantially disclosed herein incombination with any one or more other features as substantiallydisclosed herein.

Any one of the aspects/features/embodiments in combination with any oneor more other aspects/features/embodiments.

Use of any one or more of the aspects or features as disclosed herein.

It is to be appreciated that any feature described herein can be claimedin combination with any other feature(s) as described herein, regardlessof whether the features come from the same described embodiment.

The details of one or more aspects of the disclosure are set forth inthe accompanying drawings and the description below. Other features,objects, and advantages of the techniques described in this disclosurewill be apparent from the description and drawings, and from the claims.

The phrases “at least one”, “one or more”, and “and/or” are open-endedexpressions that are both conjunctive and disjunctive in operation. Forexample, each of the expressions “at least one of A, B and C”, “at leastone of A, B, or C”, “one or more of A, B, and C”, “one or more of A, B,or C” and “A, B, and/or C” means A alone, B alone, C alone, A and Btogether, A and C together, B and C together, or A, B and C together.When each one of A, B, and C in the above expressions refers to anelement, such as X, Y, and Z, or class of elements, such as X₁-X_(n),Y₁-Y_(m), and Z₁-Z_(o), the phrase is intended to refer to a singleelement selected from X, Y, and Z, a combination of elements selectedfrom the same class (e.g., X₁ and X₂) as well as a combination ofelements selected from two or more classes (e.g., Y₁ and Z_(o)).

The term “a” or “an” entity refers to one or more of that entity. Assuch, the terms “a” (or “an”), “one or more” and “at least one” can beused interchangeably herein. It is also to be noted that the terms“comprising”, “including”, and “having” can be used interchangeably.

The preceding is a simplified summary of the disclosure to provide anunderstanding of some aspects of the disclosure. This summary is neitheran extensive nor exhaustive overview of the disclosure and its variousaspects, embodiments, and configurations. It is intended neither toidentify key or critical elements of the disclosure nor to delineate thescope of the disclosure but to present selected concepts of thedisclosure in a simplified form as an introduction to the more detaileddescription presented below. As will be appreciated, other aspects,embodiments, and configurations of the disclosure are possibleutilizing, alone or in combination, one or more of the features setforth above or described in detail below.

Numerous additional features and advantages of inventive concepts willbecome apparent to those skilled in the art upon consideration of theembodiment descriptions provided hereinbelow.

BRIEF DESCRIPTION OF THE FIGURES

The accompanying drawings are incorporated into and form a part of thespecification to illustrate several examples of the present disclosure.These drawings, together with the description, explain the principles ofthe disclosure. The drawings simply illustrate preferred and alternativeexamples of how the disclosure can be made and used and are not to beconstrued as limiting the disclosure to only the illustrated anddescribed examples. Further features and advantages will become apparentfrom the following, more detailed, description of the various aspects,embodiments, and configurations of the disclosure, as illustrated by thedrawings referenced below.

FIG. 1 illustrates a block diagram of a system according to at least oneexample embodiment.

FIG. 2 illustrates block diagrams for a sensor node and a sensor hubaccording to at least one example embodiment.

FIG. 3 illustrates an example implementation of certain elements in thesystem in FIG. 1 according to at least one example embodiment.

FIG. 4 illustrates another example implementation of certain elements inthe system in FIG. 1 according to at least one example embodiment.

FIG. 5 illustrates yet another example implementation of certainelements in the system in FIG. 1 according to at least one exampleembodiment.

FIG. 6 illustrates an additional example implementation of certainelements in the system in FIG. 1 according to at least one exampleembodiment.

FIG. 7 illustrates an example of a local structure according to at leastone example embodiment.

FIG. 8 illustrates various views of a sensor package according to atleast one example embodiment.

FIG. 9 illustrates a system with sensor(s) being incorporated into orbetween typical layers of roof according to at least one exampleembodiment.

FIG. 10 illustrates a method for a sensor system according to at leastone example embodiment.

DETAILED DESCRIPTION

The ensuing description provides example embodiments, and is notintended to limit the scope, applicability, or configuration of theclaims. Rather, the ensuing description will provide those skilled inthe art with an enabling description for implementing the describedembodiments. Various changes may be made in the function and arrangementof elements without departing from the spirit and scope of the appendedclaims.

It should be understood that various aspects disclosed herein may becombined in different combinations than the combinations specificallypresented in the description and accompanying drawings. It should alsobe understood that, depending on the example or embodiment, certain actsor events of any of the processes or methods described herein may beperformed in a different sequence, and/or may be added, merged, or leftout altogether (e.g., all described acts or events may not be necessaryto carry out the disclosed techniques according to different embodimentsof the present disclosure). In addition, while certain aspects of thisdisclosure are described as being performed by a single module or unitfor purposes of clarity, it should be understood that the techniques ofthis disclosure may be performed by a combination of units or modulesassociated with, for example, a computing device.

It will be appreciated from the following description, and for reasonsof computational efficiency, that the components of the system(s) hereincan be arranged at any appropriate location within a distributed networkof components without impacting the operation of the system(s).

Furthermore, it should be appreciated that the various links connectingthe elements can be wired, traces, or wireless links, or any appropriatecombination thereof, or any other appropriate known or later developedelement(s) that is capable of supplying and/or communicating data to andfrom the connected elements. Transmission media used as links, forexample, can be any appropriate carrier for electrical signals,including coaxial cables, copper wire and fiber optics, electricaltraces on a PCB, or the like.

As used herein, the phrases “at least one,” “one or more,” “or,” and“and/or” are open-ended expressions that are both conjunctive anddisjunctive in operation. For example, each of the expressions “at leastone of A, B and C,” “at least one of A, B, or C,” “one or more of A, B,and C,” “one or more of A, B, or C,” “A, B, and/or C,” and “A, B, or C”means A alone, B alone, C alone, A and B together, A and C together, Band C together, or A, B and C together.

The terms “determine,” “calculate,” and “compute,” and variationsthereof, as used herein, are used interchangeably and include anyappropriate type of methodology, process, operation, or technique.

Various aspects of the present disclosure will be described herein withreference to drawings that may be schematic illustrations of idealizedconfigurations.

Unless otherwise defined, all terms (including technical and scientificterms) used herein have the same meaning as commonly understood by oneof ordinary skill in the art to which this disclosure belongs. It willbe further understood that terms, such as those defined in commonly useddictionaries, should be interpreted as having a meaning that isconsistent with their meaning in the context of the relevant art andthis disclosure.

As used herein, the singular forms “a,” “an,” and “the” are intended toinclude the plural forms as well, unless the context clearly indicatesotherwise. It will be further understood that the terms “include,”“including,” “includes,” “comprise,” “comprises,” and/or “comprising,”when used in this specification, specify the presence of statedfeatures, integers, steps, operations, elements, and/or components, butdo not preclude the presence or addition of one or more other features,integers, steps, operations, elements, components, and/or groupsthereof. The term “and/or” includes any and all combinations of one ormore of the associated listed items.

As described in more detail below, inventive concepts are directed tomethods, devices, and systems for impact detection and reporting forstructure envelopes (also called building envelopes). Insurance carriersand commercial/residential real estate owners have interests in trackingthe integrity of structures on their real estate. At least one exampleembodiment provides methods, devices, and/or systems that accuratelycapture, in real-time, impacts to structures caused by hail, fallingobjects (trees, powerlines, etc.), and/or the like. At least one exampleembodiment further comprises methods, devices, and/or systems to reportthe impacts to a local and/or remote entity.

Inventive concepts provide, among other things, a sensing system orsensor system that may be incorporated as part of a structure, forexample, on a roof of the structure to detect impacts for damageassessment and reporting purposes. In one embodiment, the sensing systemmay include a sensor layer having a network of impact sensors that isprovided between a deck layer and an underlayment layer of a roof.Additionally or alternatively, the sensor layer may be integrated withany other layer on the roof, for example, integrated with theunderlayment layer and/or integrated with the shingles or otheroutermost covering.

The impact sensors may comprise any known type of electrical,mechanical, and/or electromechanical sensor that detects impact,vibration, or mechanical shock, for example, piezoelectric sensors,piezoresistive sensors, accelerometers, capacitive sensors, strain-gaugesensors, optical sensors, pressure sensors, force-sensitive resistors,etc.

The network of impact sensors may be distributed at desired intervalsand/or in a desired pattern (e.g., in a matrix) throughout the sensorlayer or in certain portions of the sensor layer according to designpreferences. The network of impact sensors may include sub-sections ofimpact sensors that are independent from other sections of impactsensors to provide more localized impact detection and reporting for thestructure. The network of impact sensors may convert detected impactsinto electrical signals that are reported to and/or stored at a localand/or remote processing device (or processor) via any known wiredand/or wireless communication method. The network of impact sensors mayinclude more or fewer sensor areas of the structure depending on a levelof sensitivity desired for the areas of the structure. For example,areas of the structure that are more vulnerable to impacts (e.g., areasunder trees or other hazards) may include a higher density of impactsensors compared to areas of the structure that are less vulnerable toimpacts.

As noted above, the network of impact sensors may include or beconnected to a local processing device (e.g., a smart home system, amobile phone, a sensor hub, etc.) that receives the electrical signalsand analyzes the electrical signals (e.g., via a mobile phone app orother program) to determine characteristics associated with the detectedimpacts, which may then be reported to an interested entity such asproperty owner, an insurance carrier, other interested parties (realestate advertisers, prospective home buyers, shingle manufacturer,weather services, etc.), and/or the like. The interested entity maychoose to further process the data (via a processing device) and/or drawconclusions regarding a level of damage, remaining life of shingles,insurance costs, etc. For example, the processing device may draw fromhistorical data/profiles of impacts to other structures to determine alevel of damage, remaining life of shingles and/or insurance costs.Additionally or alternatively, unanalyzed electrical signals may bepassed from a local transmitting device at or near the network of impactsensors through a communication network to a remote processing devicefor further analysis. In one embodiment, the electrical signals may beanalyzed by the local processing device and any results of the analysismay be sent to the remote processing device or other remote entity. Thecommunication network may be wired and/or wireless, as desired, and useany known wired and/or wireless communication standards, methods, etc.

The processing device (remote and/or local) may assign metadata to eachdetected impact. The metadata may include the time/date of the detectionand other statistics associated with the impact such as size, force,and/or any other property of the impact that interested entities mayfind useful.

In at least one example embodiment, the interested entities may benotified upon detection of impacts, for example, if the detected impactsare determined by the processing device to possibly cause damage to thestructure. The notification may be audible and/or visual. For example,the notification may be in the form of an email, an SMS message, amechanical flag (similar to a circuit breaker), a sound alarm, and/orthe like.

In at least one example embodiment, the processing device creates animpact history profile, for example, in the form of a table thatincludes a log of detected impacts and associated metadata.

In at least one example embodiment, the processing device generates aheatmap of the detected impacts that includes different colors toindicate different levels of impact so that localized impacts are easilydistinguished on the structure. The processing device may store theheatmap as part of the impact history profile. In at least one exampleembodiment, the heatmap may be created in response to one or moreconditions, such as when a frequency of detected impacts occurs morethan a threshold frequency and/or when the detected impacts are over athreshold level of impact.

The impact sensors may be designed so as to detect only impacts that areabove a desired threshold amount of impact. Additionally oralternatively, the impact sensors may be designed so as to detect nearlyall impacts, and then the processing device may filter out those impactsthat are above a desired threshold amount of impact and/or that occurmore a desired threshold frequency for further processing and/orreporting.

In operation, an impact sensor may convert an impact into an electricalsignal having a signal characteristic (amplitude, frequency, phase,wavelength, etc.) that is based on the impact. For example, the impactsensor may convert the impact into an electrical signal having anamplitude that is larger for stronger impacts and smaller for weakerimpacts. The processing device (remote and/or local) may determinewhether the amplitude of the electrical signal is above a thresholdamplitude. If so, the processing device may perform full processing onthe electrical signal (e.g., assign metadata, add an entry to the impacthistory profile, add a data point to the heatmap, etc.). If not, theprocessing device may consider the detected impact as an insignificantevent and cease processing operations for that particular receivedsignal. Alternatively, the processing device may perform fewerprocessing operations on electrical signals having amplitudes that arebelow the threshold. For example, the processing device may create anentry in the impact history profile in a section designated forinsignificant impacts and assign desired metadata so that there is arecord of an impact occurring.

In at least one example embodiment, the processing device may performfull processing on the detected impacts in response to one or moreconditions, for example, when the detected impacts across a desiredsurface are occur more than a desired threshold frequency, when thedetected impact is more than a desired threshold level of impact, and/orthe like.

In at least one example embodiment, the sensing system may includeadditional sensing features, such as temperature sensing, weight sensingto detect a change in the weight of a shingle or missing roofingmaterial, etc. Such information may be included as part of the metadatadiscussed above or other information set that may prove useful forassociating temperature and/or weight changes with impact detections.

The processing device may correspond to one or many computer processingdevices. For instance, the processing device may be a processor, forexample, a Field Programmable Gate Array (FPGA), an Application-SpecificIntegrated Circuit (ASIC), any other type of Integrated Circuit (IC)chip, a collection of IC chips, a microcontroller, a collection ofmicrocontrollers, or the like. As a more specific example, the processormay be provided as a microprocessor, Central Processing Unit (CPU), orplurality of microprocessors that are configured to execute theinstructions sets stored in a memory. Upon executing the instructionsets stored in memory, the processor enables various functions of theimpact detection device/system.

The memory may include any type of computer memory device or collectionof computer memory devices. The memory may be volatile or non-volatilein nature and, in some embodiments, may include a plurality of differentmemory devices. Non-limiting examples of memory include Random AccessMemory (RAM), Read Only Memory (ROM), flash memory,Electronically-Erasable Programmable ROM (EEPROM), Dynamic RAM (DRAM),etc. The memory may be configured to store the instruction sets depictedin addition to temporarily storing data for the processor to executevarious types of routines or functions.

Inventive concepts relate to sensor nodes located inside an attic on theunderside of a roof so as to be protected from outdoor environment. Thesensor nodes may be rigidly coupled to the roof structure through, forexample a single, standard fastener for ease of installation andavailability of parts. Empirical testing may show that the number ofsensor nodes for a particular structure can be optimized with strategicattachment to structural members (e.g., beams or joists) which arethemselves coupled to the roof underlayment sheets and which tend toaggregate and couple vibrational energy from large areas. In oneembodiment, sensor nodes receive calibration and undergo functionalchecks, which may be performed in a single step with a calibrationdevice. Such a calibration device may comprise a small, hand-heldbattery-powered vibrational exciter (e.g., voice coil or eccentricmass-motor) which would output energy with a sweep of known amplitudeand spectral distribution.

The sensor nodes are distributed throughout a residence or commercialbuilding and may be connected via wired cable (e.g., standard CAT5/6Ethernet wire) which supplies both power and communication.Alternatively, the sensor nodes are battery operated with data sent overa wireless connection. In one embodiment, the sensor nodes measurevibration by sudden acceleration with an accelerometer. A variety ofalgorithms may be employed to accurately detect and classify hail events(e.g., a machine learning approach). Sensor fusion strategies may yieldadditional insight or quality of data. In addition to an accelerometer,each sensor node may include a temperature sensor, an air sensor, ahumidity sensor, a gas sensor (CO, CO2, VOCs) or particulates (smoke,dust, ash), and/or a microphone (hail events will produce significantacoustic events). A sensor node may further include pyroelectric typesensor (e.g., infrared-based) for early warning fire detection and/oridentification of abnormally hot and cold zones in an attic space. Thesensor nodes may transfer data to a sensor hub. For a wired connection,transfer can happen on event or on a scheduled basis. For a wirelessconfiguration, power savings are key for battery longevity, and so thesensor node may only transfer data after a qualified event, but may alsooutput an infrequent “heartbeat” for sensor integrity assessment. Thedata is collected and stored by the sensor hub, which may initiatetransfer of data to a central data server on a regular basis and/or uponidentification of an event. In one embodiment, the central data serverinitiates transfer from the sensor hub. The sensor hub is connected tothe LAN through Ethernet or a wireless connection or the sensor hub isconnected through cellular connection directly to central data server.If Ethernet cabling is used for power and data, a specialized sensor hubmay be avoided and replaced with a standard COTS PoE Ethernet switch.

Although example embodiments are shown and described with respect toimpact detection on a roof of a building, it should be appreciated thatinventive concepts may also be applied to other parts of the building(e.g., siding, patios, etc.) and/or other structures (e.g., vehicles,roads, bridges, floors, or any other type of structure where impactdetection is useful for the property owner or property insurer).

In view of the above, it should be understood that example embodimentsprovide methods, devices, and systems for easy detection, analysis, andreporting of impacts to structures, which may lead to increasedefficiencies for insurance carriers (fewer and/or more targetedinspections, insurance fraud identification), improved home historymetrics for property owners and/or buyers, improved weatherreporting/forecasting, and/or the like.

FIG. 1 illustrates a block diagram of a system 100 according to at leastone example embodiment. The system 100 includes a local structure 104coupled to a remote system 108 through one or more suitable wired and/orwireless connections. In one non-limiting example, the local structure104 corresponds to or includes a residential or commercial structure andthe remote system 108 corresponds to or includes a database thatreceives, stores, and/or processes data received from other elements ofthe system 100 and/or provides certain control functions for elements ofthe local structure 104. In one embodiment, the remote system 108 isassociated with an insurance provider and includes a server, acollection of servers, and/or the like. The local structure 104 and theremote system 108 may be in communication with one another over theInternet or other suitable fabric.

The local structure 104 includes one or more sensor nodes 112, a sensorhub 116, an access point 120, a power source 124, a sensor calibrator128, and one or more user devices 132.

As described in more detail below with reference to FIG. 2 , a sensornode 112 may include one or more sensors that sense various aspects ofthe environment of the local structure 104. For the environment ofexample, a sensor node 112 includes hardware and/or software for sensingvarious conditions within or surrounding a structure to which the sensornode 112 is attached. In at least one embodiment, a sensor node 112includes one or more sensors that detect impacts to the structure (e.g.,hail), ambient temperature, humidity, and/or any other suitableparameter that may be useful for gathering information about thestructure's condition or for gather other information for an interestedentity. Multiple sensor nodes 112 may be distributed throughout a singlelocal structure 104 to provide a network of sensor nodes 112. Asdiscussed in more detail below, each sensor node 112 may comprise asensor package that includes multiple sensors and, in some cases, one ormore sensor nodes have processing capabilities.

The sensor hub 116 may include suitable hardware and/or software tofunction as a centralized controller for the sensor nodes 112. As such,the sensor hub 116 may be in direct wired and/or wireless communicationwith the sensor nodes 112, which may involve the access point 120 (e.g.,a wireless router). The sensor hub 116 may enact one or more suitableprotocols to synchronize or pair each sensor node 112 to the sensor hub116, which enables the sensor hub 116 to send and receive signalsto/from sensor nodes 112 as well as uniquely identify each sensor node112 to communicate with a specific sensor node 112. In at least oneembodiment, the sensor hub 116 may query sensor nodes 112 for statusinformation about the working condition of sensors in the sensor nodes112. The sensor hub 116 may include a user interface with one or moredevices that enable user input and/or that provide user-readable output(e.g., a user interface with switches, buttons, touch displays,illuminated indicators, and/or the like).

In one embodiment, the sensor hub 116 is accessible by and itsfunctionality controlled with a user device 132 (e.g., a mobile phone)over a suitable wired or wireless link using one or more applicationsrunning on the user device 132. In this way, the sensor hub 116 may actas a gateway that allows user devices 132 to access and control aspectsof each sensor node 112. Together, the sensor nodes 112 and sensor hub116 form a sensor system 118 that may be installed at the localstructure 104 at the time of initial building or as an after-marketproduct. Stated another way, the sensor system 118 may be a proprietarysystem for tracking the condition of the local structure 104 andreporting such condition to the remote system 108 (e.g., an insuranceprovider). Although only one sensor hub 116 is shown, more sensor hubs116 may be included (e.g., for larger local structures 104).Alternatively, at least one example embodiment contemplates placing thefunctionality of the sensor hub 116 into the access point 120 and/orinto one of the sensor nodes 112 to reduce the number of sensor hubs orto completely eliminate the sensor hub 116 from the system 100. In atleast one embodiment, the sensor system 118 may further comprise theremote system 108, the sensor calibrator 128, the user devices 132, theaccess point 120, and/or the power source 124. For example, some or allcomponents of system 100 may be bundled together and sold and operatedas a bundle.

As may further be appreciated, one or more sensor nodes 112, the sensorhub 116, and/or the remote system 108 may comprise circuitry thatfacilitates communication with the sensor hub 116 and other sensor nodes112. Such circuitry may include amplification circuitry to amplifyoutgoing signals and/or incoming signals as well as codec circuitry tocode and decode outgoing and/or incoming signals to maintain a secureconnection between elements of the system 100.

In accordance with “smart home” concepts, the sensor hub 116 may receiveupdates (e.g., firmware updates from a remote server associated with thesensor hub 116, like the remote system 108). The sensor hub 116 may thendistribute corresponding updates to sensor nodes 112. The sensor hub 116may receive additional information that can be correlated with output ofthe sensor nodes 112. For example, the sensor hub 116 may receiveweather-related information (e.g., from the Internet) and correlate thisinformation with output from the sensor nodes 112 as part of verifyingthe accuracy of the output from the sensor nodes 112, assessing thecondition of the local structure 104, and/or determining whether toreport anything to the remote system 108. For example, the output of thesensor nodes 112 may be verified or enhanced by consulting externalinformation retrieved or received by the sensor hub 116. To furtherillustrate this point, consider a scenario where the output of one ormore sensor nodes 112 taken alone indicates that the local structure 104has experienced a hailstorm. In this case, external weather-relatedinformation received by the sensor hub 116 may be used to confirm ordisconfirm that a hailstorm occurred. If the externally receivedweather-related information indicates that a hailstorm has likelyoccurred, then the sensor system 118 may take steps to report the eventto the remote system 108. On the other hand, the sensor system 118 mayhold reporting when the weather-related information indicates that ahailstorm has not likely occurred, meaning that the sensor nodes 112 mayhave detected an event other than a hailstorm (e.g., an event caused byloose debris impacting the local structure 104 on a windy day).

The access point 120 may include suitable hardware and/or software forenabling wired and/or wired communication between elements of the localstructure 104 and between the local structure 104 and the remote system108. Without limitation, an access point 120 may include a wirelessrouter (e.g., Wi-Fi router), a modem that pairs with an internetprovider, a switch (e.g., an Ethernet switch), and/or other suitabledevice for exchanging data and control signals within the localstructure 104 and between the local structure 104 and the remote system108. In one non-limiting embodiment, the access point 120 may providewired communication between the local structure 104 and the remotesystem 108 over the Internet while also providing wireless communicationbetween elements of the local structure 104 (e.g., the sensor nodes 112,the sensor hub 116, the sensor calibrator 128, and/or user devices 132).

The power source 124 may provide power to one or more of the elements inthe local structure 104, such as the sensor hub 116, the sensor nodes112, the access point 120, and/or the user devices 132. For example, thepower source 124 includes one or more power outlets integrated with thelocal structure 104 (e.g., a 120V, 50 Hz-60 Hz outlet or other suitablepower outlet). In at least one embodiment, the sensor nodes 112 and/orthe sensor hub 116 receive power and communicate data over the samecable, for example, using power-over-Ethernet (PoE) Cat 5 or Cat 6cables.

The sensor calibrator 128 may be a device including hardware and/orsoftware that enables functional checks and calibration of the sensornodes 112 and/or the sensor hub 116. For example, the sensor calibrator128 may comprise a portable, battery powered device, that includes avibrational exciter such as a voice coil or eccentric mass-motor (e.g.,an eccentric rotating mass vibration motor) that outputs energy (e.g.,vibrations) with a sweep of known amplitude and spectral distribution.Upon installation of the sensor nodes 112 on the local structure 104, aninstaller of the sensor system 118 may use the sensor calibrator 128 tocalibrate or perform functional checks on the sensor nodes 112 and/orthe sensor hub 116 by comparing the known characteristics of thevibrational exciter with vibration characteristics sensed by the sensornodes 112. Calibration may include making appropriate adjustments tosensor sensitivities, sensor locations, sensor mounts, and/or the likebased on the comparison. Additionally or alternatively, calibration orfunctional checks may trigger adjustments to coefficients applied in anadaptive filtering algorithm (e.g., performed at the sensor node 112and/or at the sensor hub 116). If the sensor system 118 employs amachine learning algorithm or neural network approach, the calibrationdata may be used as training data to tailor or to optimize the sensorsystem 118 for complex mechanical nuances of the local structure 104.

The sensor calibrator 128 may remain on-site with the local structure104 after installation of the sensor system 118 for future calibrationor functional checks by an occupant of the local structure 104 or may beremoved from the local structure 104 (e.g., as property of the installerof the sensor system 118). In at least one embodiment, the sensorcalibrator 128 may be detachably connected to the sensor hub 116 in amanner that enables the sensor calibrator 128 to be stowed with sensorhub 116 as a single unit. Such connection may be purely mechanical(e.g., a snug fit or some type of lock-unlock connection) orelectro-mechanical. In the event of an electro-mechanical connection,the sensor calibrator 128 may include a rechargeable power source thatreceives a hard-wired or wireless charge when connected to the sensorhub 116 so that the sensor calibrator 128 is ready for at-will use. Suchan electro-mechanical connection may also enable the sensor calibrator128 to exchange information with the sensor hub 116 related to previousor future calibration or functional checks. The sensor calibrator 128may further receive firmware updates through an electromechanicalconnection to the sensor hub 116. In another embodiment, the sensorcalibrator 128 may be built into and not removable from a sensor node112.

In yet another embodiment, one or more sensor calibrators 128 areinstalled in the local structure 104 in the same or similar fashion asthe sensor nodes 112 so that the system can periodically run functionalchecks with ease and efficiency. An installed sensor calibrator 128 maybe in wired or wireless communication with the sensor nodes 112 and/orthe sensor hub 116 to enable data and control signals to passtherebetween. The sensor calibrator 128 may include its own set ofsensors (e.g., a vibration sensor) and provide calibration data to thesensor nodes 112 and/or the sensor hub 116 for comparison against sensordata sensed at the sensor nodes 112.

In a non-limiting example, the sensor system 118 and/or the sensorcalibrator 128 may prompt a user or an occupant of the local structure104 (through a user device 132 or other suitable audio/visual alertmechanism) to carry out periodic functional checks or calibrations toensure the sensor nodes 112 and sensor hub 116 are functioning properly.Such prompts may be issued at regular intervals based on elapsed timesince a previous calibration or functional check and/or issued atirregular intervals, for example, when the sensor hub 116 detects that asensor node 112 may be malfunctioning and/or after detection of an event(e.g., a weather event) that may have interfered with the sensorsystem's 118 ability to accurately detect and report information.

A user device 132 may include or correspond to a computing device thatenables a user to interact directly with the sensor system 118 or tointeract indirectly with the sensor system 118 through, for example, theaccess point 120. Thus, a user device 132 may include a smartphone, atablet, a laptop, a desktop, a smart speaker/display, and/or the like.As noted above, a user device 132 runs one or more applications (e.g.,made available to the user by an application server of the remote system108) that interface with the sensor system 118 so that a user canmonitor and control the sensor system 118. Additionally, a user device132 may run one or more applications or web browser instances to accessthe remote system 108 through the access point 120 and/or through acellular network so that a user can view information about the localstructure 104 as processed and stored by the remote system 108. Suchaccess to the remote system 108 may be restricted (e.g., by requiring ausername and password to be entered into an application or web browseron the user device 132).

Still with reference to FIG. 1 , the remote system 108 may include aprocessing device such as a processor 136 and memory 140. In accordancewith inventive concepts, the remote system 108 may process datagenerated by the sensor system 118 and received from the local structure104 for the purpose of drawing certain conclusions about the state orcondition of the local structure 104, scheduling repairs andinspections, estimating repair costs, notifying interested parties,and/or for other purposes not explicitly stated herein but generallyunderstood to be useful to interested parties.

The processor 136 may include processing circuitry for carrying outcomputing tasks, for example, tasks associated with generallycontrolling the sensor system 118 and/or processing signals receivedfrom the sensor system 118. The memory 140 may correspond to any type ofsuitable memory device or collection of memory devices configured tostore instructions and may be volatile or nonvolatile in nature.Examples of the memory 140 include Flash memory, Random Access Memory(RAM), Read Only Memory (ROM), solid state memory (e.g., SSDs), diskmemory (e.g., HDDs), variants thereof, combinations thereof, or thelike. In some embodiments, the memory 140 and processor 136 areintegrated into a common device (e.g., a microprocessor may includeintegrated memory). The processor 136 may comprise software, hardware,or a combination thereof. For example, the processor 136 may executeinstructions stored on memory 140 to carry out tasks of the remotesystem 108. Additionally or alternatively, the processor 136 maycomprise hardware, such as an application specific integrated circuit(ASIC). Other non-limiting examples of processing circuitry for theprocessor 136 include an Integrated Circuit (IC) chip, a CentralProcessing Unit (CPU), a General Processing Unit (GPU), amicroprocessor, a Field Programmable Gate Array (FPGA), a collection oflogic gates or transistors, resistors, capacitors, inductors, diodes, orthe like. Some or all of the processing circuitry may be provided on aPrinted Circuit Board (PCB) or collection of PCBs. It should beappreciated that any appropriate type of electrical component orcollection of electrical components may be suitable for inclusion in theprocessing circuitry.

Although not explicitly shown, it should be appreciated that theelements in FIG. 1 include suitable interfaces for facilitating wiredand/or wireless communication. Examples of suitable interfaces include,without limitation, a coaxial port, an Ethernet port, a Universal SerialBus (USB) port, an antenna, a driver circuit, a modulator/demodulator,and/or the like.

In general, it should be appreciated that sensor data generated by asensor node 112 may pass through multiple tiers of processing of varyingcomplexity. The analysis in each subsequent tier may become moreinvolved or complex. The first, lowest level, tier of processing may becarried out by a sensor node 112 for the sake of determining when toreport sensor data to the sensor hub 116. Meanwhile a second, moreinvolved level of processing, may occur at the sensor hub 116 toidentify specific events based on the sensor data from multiple sensornodes 112 and to report these events and associated data to the remotesystem 108. Finally, a third, most involved level of processing mayoccur at the remote system 108 where events and sensor data frommultiple local structures 104 are processed to determine trends and drawconclusions about the events and/or the local structures 104 (e.g.,conditions regarding a level of damage, remaining life of shingles,insurance repair costs, premium adjustments, etc.). The remote system108 may use trends within the sensor data and events collected frommultiple structures 104 to improve the capabilities of the system 100(e.g., improve the accuracy of conclusions reached by the remote system108).

In one embodiment, the remote system 108 implements one or more methodsof feedback to confirm or disconfirm the existence of a particular eventas detected by the sensor hub 116 and/or to confirm or disconfirm someother aspect associated with an event (e.g., that an inspection orrepair is needed). One such feedback mechanism may take the form ofrequesting that an occupant of a local structure 104 verify theoccurrence of a particular event as detected by the sensor hub 116and/or verify a state or condition of the local structure 104. Therequest to the occupant may take a suitable form, such as post mail, anSMS message, an email, a notification in an application on a user device132, and/or the like.

Another feedback mechanism may take the form of the remote system 108correlating a detected event with external information. For example, agiven detected event and corresponding sensor data may be timestamped atthe sensor hub 116, which enables the remote system 108 to correlateexternal information with the given detected event as part of confirmingor disconfirming the occurrence of the event. The external informationmay be used to add to the likelihood or unlikelihood that the givendetected event has actually occurred. Such external information mayinclude weather-related information from a publicly available sourceand/or information about other events and data reported from other localstructures 104 around the same time. In this case, the remote system 108may determine a forward and/or backward looking time window thatencompasses the timestamp of the given detected event. The remote system108 may additionally or alternatively determine a subset of localstructures 104 whose detected events and associated data may be relevantto verifying the occurrence of the given detected event. The size of thetime window and subset of local structures 104 may vary depending on thetype of given detected event and/or the external information. Forexample, if the given detected event is a tornado, then the size of thetime window and subset of local structures 104 may be determined basedon external information that indicates how long the tornado lasted andwhere the tornado touched down so that the remote system's 108 analysisis focused on an area of interest where the tornado occurred.

In addition to using feedback mechanisms to verify the occurrence of agiven detected event, the same or similar feedback mechanism may be usedto improve the accuracy of identifying the given detected event, forexample, at the sensor hub 116. In this case, the remote system 108 maycomprise or be in communication with a neural network or machinelearning entity that is trained with events and associated data fromlocal structures 104, feedback on the events and associated data, and/orany suitable empirical evidence that may improve the ability of thesystem 100 to accurately identify and draw conclusions about events.

As noted above, the sensor nodes 112 may collect various information atthe local structure 104 and report (e.g., through the sensor hub 116)the information to the remote system 108 that is associated with aninterested entity such as a property owner, an insurance carrier, otherinterested parties (real estate advertisers, prospective home buyers,shingle manufacturer, weather services, etc.), and/or the like. Theinterested entity may choose to further process the data at the remotesystem 108 and/or draw conclusions about the local structure 104, suchas conclusions regarding a level of damage to local structure 104,remaining roof-life of the local structure 104, repair costs, schedulingof inspections or repair, etc. For example, the remote system 108 maydraw from historical data/profiles of events at other structures todetermine a level of damage, remaining life of the roof, and/orinsurance repair costs.

In one embodiment, the remote system 108 may conduct further processingfor the purposes of end-of-life forecasting. In one specific example, aninsurance company (or roofing company, or materials supplier) informsthe property owner that a thirty-year roof should be replaced at year 15based on the recorded intensity and number of hailstorms or the like.The end-of-life forecasting may be implemented with a “percentage oflife remaining” meter that is dynamically updated based on sensor systeminputs. A visualization of the meter may even be presented to theinterested entities.

The sensor system 118 (e.g., the sensor nodes 112 and/or the sensor hub116) may assign metadata to the sensor data. For each sensor node 112and/or for each sensor within a sensor node 112, the metadata mayinclude the time/date of detected events and other statistics associatedwith the sensor data that an interested entity may find useful.

In at least one example embodiment, an interested entity is notifiedupon the sensor system 118 detecting certain events, such as impacts tothe local structure 104. For example, an interested entity may benotified of a detected event for the local structure 104 (e.g., adetected impact event to local structure 104) when the sensor system 118and/or the remote system 108 determines that the event may have causeddamage to the local structure 104. The notification may be audibleand/or visual. For example, the notification may be in the form of anemail, an SMS message, a mechanical flag (similar to a circuit breaker),a sound alarm, and/or the like. The notification may further compriselight indicators, such as a flashing or multi-colored LED on a part ofthe sensor system 118 readily visible to a user (e.g., on the sensor hub116 which may be in an interior space of the local structure 104).

In at least one example embodiment, the sensor hub 116 and/or the remotesystem 108 creates and stores an event history profile for a particularlocal structure 104. The event history profile may take the form of atable that includes a log of detected events and associated metadata. Inone embodiment, the sensor hub 116 and/or the remote system 108generates a heatmap of certain detected events, such as detectedimpacts. In this case, the heatmap may include different colors toindicate different levels of impact so that localized impacts are easilydistinguished on the local structure 104. The sensor hub 116 and/or theremote system 108 may store the heatmap as part of the event historyprofile. In at least one example embodiment, a heatmap may be created inresponse to one or more conditions, such as when a frequency of adetected event occurs more than a threshold frequency and/or when thescale or severity of a detected event exceeds a threshold severity.

FIG. 2 illustrates block diagrams for a sensor node 112 and a sensor hub116 according to at least one example embodiment.

As shown in FIG. 2 , a sensor node 112 includes a plurality of sensors200 to 224, a power supply 228, a processor 232, and a memory 236. Theplurality of sensors may include a temperature sensor 200, a humiditysensor 204, a microphone 208, an impact sensor 212, an air sensor 216, aparticulate sensor 220, and a gas sensor 224.

The temperature sensor 200 may include any suitable sensor for sensingtemperature (e.g., ambient air temperature). Non-limiting examples of atemperature sensor 200 include a thermocouple, a resistance temperaturedetector, a thermistor, a semiconductor-based IC temperature sensor,and/or the like.

The humidity sensor 204 may include any suitable sensor for sensinghumidity (e.g., relative humidity, absolute humidity, etc.).Non-limiting examples of a humidity sensor 204 include a capacitivehumidity sensor, a resistive humidity sensor, a thermal conductivityhumidity sensor, and/or the like.

The microphone 208 may include any suitable sensor for sensing sound(e.g., caused by impacts to the local structure 104), for example, byconverting sound into electrical signals. The microphone 208 may includeone more acoustic sensors. Non-limiting examples of a microphone 208include a resistive microphone, a dynamic microphone, a condensermicrophone, a ribbon microphone, and/or the like. The microphone 208 maydetect or measure potentially annoying and/or energy-wasting effectsfrom wind. For example, one or more microphones 208 of one or moresensor nodes 112 may be used to pinpoint sources of wind whistles causedby gaps in insulation or seals in the local structure 104. Themicrophone 208 may also detect sounds for alerting interested parties tothings like vibrating guy-wires, loose roof-mounted antennas, bangingshutters, other loose exterior or interior fixtures, and/or the like. Inone embodiment, the sensor system 118 flags segments of sound recordingfor further analysis by computers or humans.

The impact sensor 212 may include any suitable sensor for sensingimpacts to the local structure 104. An impact sensor 212 may compriseany known type of electrical, mechanical, and/or electromechanicalsensor that detects impact, vibration, or mechanical shock. Non-limitingexamples of an impact sensor 212 include a piezoelectric sensor, apiezoresistive sensor, an accelerometer, a capacitive sensor, astrain-gauge sensor, an optical sensor, a pressure sensor, aforce-sensitive resistor, and/or the like. The impact sensor 212 may beused to sense weight and/or the sensor node 112 may include a separateweight sensor.

The air sensor 216 may include any suitable sensor for detectingatmospheric pressure. As such, the air sensor 216 may take the form of abarometer. Non-limiting examples of the air sensor 216 include amercury-based barometer, an aneroid barometer, a micro-electromechanicalsystem (MEMS) based barometer, and/or the like.

The particulate sensor 220 may include any suitable sensor for detectingparticles in ambient air, such as smoke, dust, ash, and/or the like.Non-limiting examples of a particulate sensor 220 include sensors thatemploy light blocking, light scattering, the Coulter principle, and/orthe like to determine air quality.

The gas sensor 224 may include any suitable sensor for detecting one ormore gases, such as radon, carbon dioxide, carbon monoxide, volatileorganic compounds (VOCs), and/or the like. Non-limiting examples of agas sensor 224 include, a metal oxide-based gas sensor, an optical gassensor, an electrochemical gas sensor, a capacitance-based gas sensor, acalorimetric gas sensor, and/or the like.

Although sensors 200 to 224 are shown and described as being part of asensor node 112, one or more sensors 200 to 224 may be integrated withother parts of the system 100, such as the sensor hub 116. In oneembodiment, parameters sensed by certain ones of the sensors 200 to 224may be additionally or alternatively be retrieved from an externalsource. For example, weather related-information such as temperature,humidity, air pressure, and/or particulate levels do not need to bedirectly sensed at the location structure 104. Instead, such informationmay be retrieved from a source external to the local structure 104 thatprovides weather-related information. In this case, the sensor hub 116may retrieve weather-related information from the remote system 108 orfrom publicly accessible sites on the Internet (e.g., from the NationalWeather Service) that track weather for the region in which the localstructure 104 resides and associate this information with parameterssensed by other sensors of the sensor nodes 112. In another scenario, asensor node 112 and/or a sensor hub 116 may receive weather-relatedinformation such as temperature, humidity, air pressure, and/orparticulate levels from a source that is external to the sensor node 112and the sensor hub 116 but local to the local structure 104. Here, thesource of the more localized weather-related information may be aweather beacon or sensors on site at the local structure 104 that arecapable of sensing weather-related information and passing the sensedinformation to the sensor nodes 112 and/or the sensor hub 116 over awired and/or wireless connection (e.g., a Wi-Fi connection).

It should be appreciated that more or fewer sensors may be included in asensor node 112 and that each sensor node 112 may comprise the same setof sensors or different sets of sensors. For example, one sensor node112 in a grouping of sensor nodes 112 for a particular structure 104 maybe the “master” sensor node that senses certain parameters that arelikely to be the same or similar across multiple sensor nodes 112. Asingle, master, sensor node 112 may sense temperature, humidity, airpressure, particulates, and/or any other parameters that are likely tobe the same or close to the same for all sensor nodes 112. In addition,sensors other than those shown and described in FIG. 2 may be includedin a sensor node 112. Sensor data processing by the master sensor nodemay also be used to trigger collection of sensor data by one or moreother, subordinate, sensor nodes. For example, one master sensor nodemay be in an “always on” or “monitoring” state while other nodes in thesystem are in an off-state, or a low-power, sleep state. The mastersensor node may “wakeup” the subordinate sensor nodes upon collectingsensor data that could be indicative of an event that would warrantcollection of sensor data by the subordinate sensor nodes. The processor232 of the master sensor node may wakeup other sensor nodes wirelesslyand/or through a wired connection.

In another embodiment, a sensor node 112 may include circuitry coupledto the processor 232 that maintains the processor 232 in a low powerstate or an off state until output of a sensor in the sensor node 112triggers the processor 232 to wake up and start processing the outputfrom the sensor and/or other sensors of the sensor node 112. Suchcircuitry may be electromechanical in nature and/or may use energyderived from the sensed parameter to trigger the wakeup process. Forexample, mechanical and/or electrical energy generated by impactsdetected by the impact sensor 212 may be harvested and used to toggle amechanical or electrical switch that couples and decouples the processor232 to the power supply 228.

The power supply 228 may comprise suitable hardware and/or software forsupplying power to elements of the sensor node 112, for example, to theprocessor 232 and/or one or more of the sensors if such sensors requirepower. In one embodiment, the power supply 228 may comprise anappropriate converter (e.g., a buck converter, an AC-DC converter)and/or a regulator (e.g., a voltage regulator) for converting a powersignal received over a hardwired line from power source 124 of the localstructure 104 into a power signal suitable for the device being powered.In another embodiment, the power supply 228 may comprise one or morebatteries (rechargeable or non-rechargeable) as a main power source oras a backup power source for the sensor node 112 for when the powersource 124 is inoperable or unavailable. In yet another embodiment, thepower supply 228 may be at least partially external to the sensor node112 and capable of generating “green” power. For example, the powersupply 228 may comprise solar panels, wind-harnessing structures, and/orother suitable renewable energy harvesters that provide power for one ormore of the sensor nodes 112 on the structure 104.

The processor 232 may comprise the same or similar structure as theprocessor 136 in FIG. 1 while the memory 236 may comprise the same orsimilar structure as the memory 140 in FIG. 1 . In general, theprocessor 232 controls sensors of the sensor node 112 and controlscommunication between the sensor node 112 and external elements, such asthe sensor hub 116, other sensor nodes 112, and/or the remote system108.

The memory 236 may store sensor data from sensors of the sensor node 112while the processor 232 may perform some low-level pre-processing of thesensor data prior to sending to the sensor hub 116 and/or the remotesystem 108. For example, the processor 232 may pre-process sensor dataas part of determining whether to report the sensor data to the sensorhub 116 and/or the remote system 108. The processor 232 may withholdreporting sensor data unless one or more thresholds are met or exceeded,which may avoid unnecessary reporting and reduce power consumption.

In some embodiments, the one or more thresholds are associated with thesensor data so that the processor 232 reports only potentially usefulsensor data back to the sensor hub 116 and/or the remote system 108. Forexample, if sensor data from one or more sensors (e.g., microphone 208and impact sensor 212) exceed respective thresholds that are associatedwith the presence of a storm (e.g., hailstorm), then the processor 232may report all or selected sensor data back to the sensor hub 116 and/orthe remote system 108.

Additionally or alternatively, the one or more thresholds are associatedwith a parameter or parameters other than the sensor data. For example,the one or more thresholds may correspond to an elapsed amount of timesince the last report from a sensor node 112 so that the sensor node 112reports sensor data at specified intervals. Upon successful completionof reporting sensor data to the sensor hub 116 and/or the remote system108, the processor 232 may erase the reported sensor data from memory236. The one or more thresholds may be design parameters set based onempirical evidence and/or preference. The one or more thresholds may bepreprogrammed into the processor 232 prior to installation and/orprovided by the sensor hub 116 and/or the remote system 108. In at leastone embodiment, the one or more thresholds are updated, for example,under control of the remote system 108 to improve filtering of thesensor data from a sensor node 112.

Still with reference to FIG. 2 , the sensor hub 116 may include aprocessor 236, memory 240, and a power supply 244. The processor 236,the memory 240, and the power supply 244 may comprise the same orsimilar structure as the processor 136, memory 140, and power supply244, respectively. As noted above, the sensor hub 116 may carry out asecond tier of processing functions for the sensor data received frommultiple sensor nodes 112, where such sensor data has undergonefiltering process at the sensor nodes 112.

In more detail, the processor 236 may be capable of identifying eventsbased on the sensor data received from sensor nodes 112. For example,the processor 236 may compare the sensor data received from one or moresensors of a sensor node 112 to reference data, and identify an eventbased on the comparison. The reference data may be preprogrammed intothe sensor hub 116 prior to installation and/or provided by the remotesystem 108. In general, the processor 236 consults the reference data todistinguish between events, identify events, and then report or notreport the events based on these determinations. Stated another way, theprocessor 236 is capable of identifying events based on the sensor dataand the reference data. The identified events may then be reported ornot reported to the remote system 108 based on factors such as theseverity of the identified event.

By way of example, some impacts sensed by the impact sensor 212 may beassociated with events not worth reporting to the sensor hub 116 and/orthe remote system 108. For example, a person walking on a roof of thelocal structure 104 may be detected by the impact sensor 212 andreported to the sensor hub 116 after passing the first tier ofprocessing at a sensor node 112. However, in some cases, this type ofevent (walking on the roof) does not warrant further analysis of sensordata at the remote system 108. On the other hand, some impacts sensed bythe impact sensor 212 are associated with events that are worthreporting. For example, hail impacts may be detected by the impactsensor 212 and reported to the sensor hub 116 after passing the firsttier of processing at a sensor node 112. Typically, a hailstorm event isworth reporting to the remote system 108. In this case, the processor232 consults the reference data to determine whether detected impactsfrom impact sensor 212 are likely associated with a person walking onthe roof or with a hailstorm, and then reports or does not report theevent accordingly.

In general, the reference data may include historical data for the localstructure 104 or historical data for multiple local structures 104. Suchhistorical data associates particular events with sensor data fromsensors of sensor nodes 112. By way of explanation and with reference tothe above-discussed impact example, the reference data reference values,ranges of reference values, and/or rules known or suspected to exist fora given event (e.g., hailstorm, fallen tree or limb, windstorm,flooding, and/or the like). Table 1 illustrates an example set ofreference data for Events 1 to N.

TABLE 1 Reference data Walking on roof event Hailstorm event (Event 1)(Event 2) . . . . . . Event N Reference value or range for Referencevalue or range for Reference value or range for data from sensors ofsensor data from sensors of sensor data from sensors of sensor type 1type 1 type 1 Reference value or range for Reference value or range forReference value or range for data from sensors of sensor data fromsensors of sensor data from sensors of sensor type 2 type 2 type 2Reference value or range for Reference value or range for Referencevalue or range for data from sensors of sensor data from sensors ofsensor data from sensors of sensor type 3 type 3 type 3 Reference valueor range for Reference value or range for Reference value or range fordata from sensors of sensor data from sensors of sensor data fromsensors of sensor type 4 . . . type 4 . . . type 4 . . . . . . Referencevalue or range . . . Reference value or range . . . Reference value orrange for data from sensors of for data from sensors of for data fromsensors of sensor type N sensor type N sensor type N Rule sets 1 to NRule sets 1 to N Rule sets 1 to N

As shown in Table 1, a particular event may be correlated withreferences values or ranges of references values for particular sensortypes within sensor nodes 112. For example, the reference data may takethe form of a table that labels events 1 to N with names that areindicative of the detected event (e.g., hailstorm, walking on roof,tornado, flooding, other). Sensor types 1 to N refer to the types ofsensors in the sensor nodes 112, and the reference values or ranges ofreference values in Table 1 may be compared to the sensor data receivedfrom the sensor nodes 112. For example, the reference value or range ofreference values for sensor type 1 may be temperature values forcomparison against sensor data from temperature sensor 200, thereference value or range of reference values for sensor type 2 may behumidity values for comparison against sensor data from humidity sensor204, and so on for each sensor type in the sensor nodes 112.

Sensor data from each sensor of a sensor node 112 is indicative of avalue of a sensed parameter (temperature, humidity, etc.). The value ofeach sensed parameter may be compared a single reference value in thereference data and/or to a range of reference values in the referencedata for the purpose of identifying an event. An event is identifiedwhen the value of each sensed parameter meets certain criteriaassociated with the single reference value and/or the range of referencevalues for that particular event (e.g., the values of all sensedparameters during a time period fall within respective reference rangesfor the parameters associated with a particular event in the referencedata, then identify the particular event). The reference values andranges and types of sensed parameters being analyzed may vary dependingon the event.

Table 1 further illustrates Rule sets 1 to N for each type of event 1 toN. In at least one embodiment, the rule sets define respective rulesthat must be met for a particular type of event to be identified. In oneexample, the rules take the form of logic statements that must assessedbefore a particular event is identified. The logic statements may beconsidered alone or in combination with the reference values or rangesof reference values to identify an event. Stated another way, a rule setby itself may be used to identify an event, or a rule set and thereference values may be used to identify an event. An example rule setmay adhere to the following logic: “if number of impacts detected bysensor nodes 112 exceeds the number X within time period Y AND sensordata from microphones 208 is consistent with the sound of hail duringtime period Y, then detect a hailstorm event.” Other rule sets may beimplemented within the same event and the rule sets may vary dependingupon the type of event being identified. Upon detecting or identifyingan event, the sensor hub 116 may send the identified event and selecteddata associated with the identified event to the remote system 108 forfurther processing. If a set of sensor data does not fall into one ofthe categories of events in the reference data, the sensor hub 116 mayassociate the sensor data with an “other” event, which may be reportedto the remote system 108 (e.g., for possible identification of an event)and/or stored at the sensor hub 116 in case another set of sensor dataproduces a similar result. Alternatively, if an event is not identifiedfor a particular set of sensor data, then the sensor hub 116 may erasethat sensor data from memory and take no further action in terms ofreporting to the remote system 108. In one example, the sensor hub 116may provide feedback to the sensor nodes 112 to adjust how the sensornodes are reporting sensor data (e.g., adjust the thresholds for sensorsof the sensor nodes 112 so that irrelevant sensor data does not pass thefirst filtering level at the sensor nodes 112, thereby reducing the useof processing and power resources of the sensor hub 116).

FIG. 3 illustrates an example implementation of certain elements in thesystem in FIG. 1 , referred to in FIG. 3 as system 100 a. The system 100a comprises sensor nodes 112, sensor hub 116, power source 124, a routeror access point 120, and a data center or remote system 108. As may beappreciated, the system 100 a relates to a fully wired system where thesensor hub 116 provides power and data communication to a single sensornode 112 over a wired connection (e.g., with power over Ethernet usingCAT 5 or CAT 6 cables). The single sensor node 112 is then linked withother sensor nodes 112 with the same or similar wired connection.Similarly, the sensor hub 116 is in communication with the router 120and data center 108 over a wired connection, such as an Ethernetconnection or other suitable connection. In the configuration of FIG. 3, each sensor node 112 may be addressable by the sensor hub 116 througha mapping of addresses to sensor nodes 112 stored at the sensor hub 116.In other words, the sensor hub 116 has the capability to communicatewith an individual sensor node 112 in the chain of sensor nodes 112 viaa suitable addressing technique. Each sensor node 112, then, maycomprise circuitry to determine whether a received signal is intendedfor that particular sensor node by checking whether an address oridentifier in the received signal matches an address or identifier ofthat sensor node 112. If so, then the received signal is processed bythat sensor node 112, and if not, then the received signal is passed tothe next sensor node 112 in the chain until the correct sensor node 112is reached.

Although the system 100 a illustrates that only one sensor node 112 isdirectly connected to sensor hub 116, more than one sensor node 112 maybe directly connected to sensor hub 116.

FIG. 4 illustrates an example implementation of certain elements in thesystem in FIG. 1 , referred to in FIG. 4 as system 100 b. The system 100b comprises sensor nodes 112, sensor hub 116, power source 124, a routeror access point 120, and a data center or remote system 108. System 100b is substantially the same as system 100 a except that the sensor hub116 and the router 120 communicate wirelessly, for example, over asuitable wireless connection such as a Wi-Fi connection, near-fieldcommunication (NFC) connection, Bluetooth connection, and/or the like.

FIG. 5 illustrates an example implementation of certain elements in thesystem in FIG. 1 , referred to in FIG. 5 as system 100 c. The system 100c comprises sensor nodes 112, sensor hub 116, power source 124, a routeror access point 120, and a data center or remote system 108. System 100c is substantially the same as system 100 a except that the sensor nodes112 are battery powered and communicate wirelessly with one anotherand/or with the sensor hub 116. As in FIG. 4 , the sensor hub 116 andthe router 120 also communicate wirelessly. Suitable wirelessconnections between sensor nodes 112, sensor hub 116, and router 120include a Wi-Fi connection, near-field communication (NFC) connection,Bluetooth connection, and/or the like.

FIG. 6 illustrates an example implementation of certain elements in thesystem in FIG. 1 , referred to in FIG. 6 as system 100 d. The system 100d comprises sensor nodes 112, sensor hub 116, power source 124, and adata center or remote system 108. System 100 d is substantially the sameas system 100 a except that the sensor hub 116 and the data center 108communicate wirelessly, for example, over a suitable cellular wirelessconnection such as a 3G cellular connection, an LTE (4G) cellularconnection, a 5G cellular connection, and/or the like. The cellularcommunication between the sensor hub 116 and data center 108 obviatesthe need for a separate router or access point 120, although it shouldbe appreciated that multiple cellular towers may be in the transmissionpath between sensor hub 116 and data center 108.

Although the systems 100 a to 100 d have been described separately, itshould be appreciated that the configurations shown therein may becombined with one another in any suitable fashion. For example, thesensor nodes 112 may comprise a combination of nodes that communicatewirelessly and nodes that communicate over a wired connection. Such animplementation may be useful where additional sensor nodes 112 withwireless capabilities are added to an existing system that includeswired sensor nodes 112 to form an ad-hoc network of sensor nodes 112using wired and wireless communication.

FIG. 7 illustrates an example of a local structure 104 according to atleast one example embodiment. More specifically, FIG. 7 is a top view ofa structure envelope (i.e., the roof) of a local structure 104. Asshown, seven sensor nodes 112 (in any suitable configuration orcombination thereof from FIGS. 3-6 ) are distributed throughout thestructure 104. In this example, the local structure 104 has one sensornode per separately formed roof structure (the roof structure at the topof the figure without a sensor node 112 may be an entryway or otherstructure that is not of interest for monitoring). The sensor nodes 112may be fixed to the local structure 104 in accordance with thediscussion of FIG. 8 below, where a sensor package having the componentsof a sensor node 112 is mounted to beams, joists, or deck layer (e.g.,plywood that laid over beams of a roof) of the local structure 104.These components are considered useful because these areas tend toaggregate and couple vibrational energy from large areas. However,example embodiments are not limited thereto, and a number and locationof sensor nodes 112 may vary according to the size and/or shape of thelocal structure 104. In at least one embodiment, a type of calibrationprocess may be performed at or prior to installation of the sensor nodes112 to determine the number and/or locations of sensor nodes 112. Here,the calibration device 128 may be useful for simulating impacts inmanner that enables an installer of the system to gather information onwhere a sensor node 112 should be located.

FIG. 8 illustrates various views of a sensor package 800 according to atleast one example embodiment. In general, a sensor package 800 comprisesan injection-molded housing (made of some thermoplastic such as ABS)with a clamshell-style construction and appropriate fasteners to hold ittogether. A sensor package 800 further comprises a PCB assembly, whichcontains active circuitry, such as an Ethernet jack (RJ-45) forconnection to a network and source of power (derived from PoE), amicrocontroller, an accelerometer for sensing vibrations from hail orother impact events of interest, a combination temperature and humiditysensor (coupled to the attic environment with an appropriate port on thetop of the housing), a microphone and appropriate conditioning circuitry(since hail impacts will produce considerable noise, acoustic sensingmay be a valuable secondary metric of hail intensity and frequency), andan LED, useful for status information during commissioning andmaintenance. The sensor package also includes an anchor mechanism whichallows a standard fastener to attach the device to the underside of aroofs wood underlayment (e.g., 0.75″ thick plywood).

In accordance with at least one embodiment, each sensor node 112 has allor some of its components contained in a sensor package 800. Statedanother way, each sensor node 112 in FIGS. 1-7 may correspond to asingle sensor package 800.

As shown in FIG. 8 , a sensor package 800 includes a housing 804 thathouses one or more of the components of a sensor node 112 in FIG. 2 .For example, the sensors, power supply, processor, and/or memory of eachsensor node 112 in FIG. 2 may be laid out on a PCB (not shown) mountedin the sensor package 800. One end of the housing 804 comprises aconnection portion 808 that projects from the end of the housing 804 andthat includes an opening for a connection mechanism 812 embodied in FIG.8 . A bottom surface 816 of the housing 804 may be planar across theentire bottom surface 816 (including a bottom surface of the connectionportion 808) so that the bottom surface 816 is flush with a surface of amounting member 820 when mounted to the mounting member 820. In oneembodiment, the mounting member 820 corresponds to a joist, a beam, or adeck layer of a roof of a local structure 104. As shown in FIG. 8 , thescrew 812 is screwed into the mounting member 820 to secure the sensorpackage in place. A sensor package 800 is mounted to a part of the localstructure 104 that enables the impact sensor 212 to sense impacts to animpact receiving surface of a structure envelop of the local structure104 and/or other vibrations induced on the structure envelope of thelocal structure 104. Stated another way, a sensor package 800, whichcorresponds to a sensor node 112, is in force-transmitting contact withan impact receiving surface of a structure envelope of the localstructure 104 to sense impacts to the impact receiving surface and/orother vibrations induced on the structure envelope of the localstructure 104. The impact receiving surface may correspond to a surfaceof an outermost layer of the structure envelope, such as the exteriorsurface of singles or exterior surface of another layer of roofingmaterial.

Another end of the housing 804 includes an interface 824 incorporatedinto the end of the housing 804, which is illustrated as an RJ-45connector for Ethernet cables (e.g., Cat 6 and Cat 5 cables). However,example embodiments are not limited thereto, and the interface 824 maycomprise any suitable interface for enabling communication and/or powertransfer (e.g., a USB cable). In addition, a sensor package 800 maycomprise multiple interfaces 824 to accommodate multiple means ofcommunication and/or power transfer. In at least one embodiment, theinterface 824 is omitted or remains unused, for example, when a sensornode 112 communicates wirelessly and operates on battery power.

The bottom surface 816 of the housing 804 may include connectors 828 ato 828 d, embodied as screws or rivets that secure a face plate 832 ofthe housing 804 to a main body of the housing 804 (the face plate 832and the main body of the housing 804 form a clamshell-style piece). Inone embodiment, the components of a sensor node 212 are mounted on a PCBwhich is in turn mounted to the face plate 832.

A top surface 836 of the housing 804 includes windows or ports 840 and844 and an indicator 848. In one embodiment, port 840 provides a pathfor sound outside of the housing 840 to reach the microphone 208.Similarly, port 844 provides a window for the air sensor 216 and/or ahumidity sensor 208. Indicator 848 may comprise one or more LEDs (lightemitting diodes) that is used for communicating status information aboutthe sensor node 112.

As may be appreciated, FIG. 8 illustrates one example of a sensorpackage 800 and that variations of the sensor package 800 are within thescope of inventive concepts. For example, the sensor package may includemore or fewer of certain elements, such as more or fewer fasteners, moreor fewer ports and/or indicators, and/or more or fewer interfaces.

FIG. 9 illustrates a system 900 with sensor(s) being incorporated intoor between typical layers of roof according to at least one exampleembodiment. The sensor(s) may be the same of similar sensors as in thesensor nodes 112. As shown, the sensors in FIG. 9 may be part of asensor layer 904 having a network of sensors provided between a decklayer and an underlayment layer of a roof. Additionally oralternatively, the sensor layer 904 may be integrated with any otherlayer on the roof, for example, integrated with the underlayment layerand/or integrated with the shingles or other outermost covering. In anyevent, sensors of the sensor layer 904 are in force-transmitting contactwith an impact surface of the roof, which corresponds to the layer ofshingles in FIG. 9 .

In accordance with example embodiments, the sensors of the sensor layer904 may comprise, among other sensors, impact sensors may comprise anyknown type of electrical, mechanical, and/or electromechanical sensorthat detects impact, vibration, or mechanical shock, for example,piezoelectric sensors, piezoresistive sensors, accelerometers,capacitive sensors, strain-gauge sensors, optical sensors, pressuresensors, force-sensitive resistors, etc.

A network of impact sensors may be distributed at desired intervalsand/or in a desired pattern (e.g., in a matrix) throughout the sensorlayer 904 or in certain portions of the sensor layer according to designpreferences. The network of impact sensors may include sub-sections ofimpact sensors that are independent from other sections of impactsensors to provide more localized impact detection and reporting for thestructure. The network of impact sensors may convert detected impactsinto electrical signals that are reported to and/or stored at a localand/or remote processing device (or processor) via any known wiredand/or wireless communication method. The network of impact sensors mayinclude more or fewer sensor areas of the structure depending on a levelof sensitivity desired for the areas of the structure. For example,areas of the structure that are more vulnerable to impacts (e.g., areasunder trees or other hazards) may include a higher density of impactsensors compared to areas of the structure that are less vulnerable toimpacts.

The sensor layer 904 may include separate non-contiguous portions thatare installed at certain locations on the structure envelope in the sameor similar manner as shown in FIG. 7 .

The sensor layer 904 may be substituted for the sensor nodes 112 in theprevious figures and/or may supplement the sensor nodes 112. Thus, thesystem 900 may include the same or similar elements and operate in thesame or similar manner as that described above with reference to FIGS.1-8 .

FIG. 10 illustrates a method 1000 for a sensor system according to atleast one example embodiment. More specifically, the method 1000 may beperformed for a sensor system 118 that processes sensor data in a tieredfashion to reduce power consumption and unnecessary network trafficwhile improving the accuracy and efficiency of backend processes for aninterested entity (e.g., an insurance company, property owner, etc.).The method 1000 may be performed by one or more of the elementsdescribed above with reference to FIG. 9 .

Operation 1004 includes producing, by a sensor of a first node of asensor system, first sensor data associated with a structure envelope ofthe structure. The sensor may correspond to one of the sensors in FIG. 2(e.g., an impact sensor 212) and be in force-transmitting contact withan impact receiving surface of the structure envelope. The structure maycorrespond to local structure 104 while the structure envelope maycorrespond to a roof or other part of the local structure 104 that hasan impact surface receiving surface exposed to the outside environment.The sensor system may correspond to sensor system 118 with the firstnode corresponding to a sensor node 112. The first sensor data is dataor sensor signals output from the sensor to, for example, the processor232. As may be appreciated, other suitable sensors from FIG. 2 may beincluded in the first node 112. In this case, the first sensor data mayinclude data from all or selected sensors in the first node 112.

Operation 1008 includes performing, at the first node 112, a first setof operations to filter out unwanted data from the first sensor data toform a first filtered dataset. In one embodiment, and as noted in thedescription of FIG. 2 , the first set of operations includes comparingthe first sensor data to one or more thresholds, and identifying data inthe first sensor data as unwanted data or as data of the first filtereddataset based on the comparison. For example, the first sensor data maybe comprised of sensor signals (e.g., raw sensor signals or lightlyprocessed sensor signals). In this case, one or more signalcharacteristics (e.g., frequency, amplitude, phase, SNR, and/or thelike) of the sensor signals are compared against one or morecorresponding thresholds for the one or more signal characteristics tofilter out unwanted data from the first sensor data. Consider an examplewhere the sensor corresponds to an impact sensor 212, and the firstsensor data comprises electronic sensor signals having amplitudes thatvary based on an amount of force detected by the impact sensor 212, thenthe first set of operations may include comparing the amplitudes of thesensor signals against a threshold amplitude, and identifying unwanteddata as those sensor signals having amplitudes that do not exceed thethreshold amplitude. Here, the first filtered dataset would then includeonly sensor signals that exceed the threshold, thereby reducing theamount of sensor data that is output from the first node 112 to, forexample, a second node of the sensor system 118 such as the sensor hub116 for another round of processing to identify an event. In oneembodiment, the unwanted data corresponds to data that is not relevantto identifying an event (e.g., a hailstorm), and the first filtereddataset corresponds to data that is relevant to identifying an event.

The first set of operations in step 1008 may further include other dataconditioning processes. For example, the first set of operations mayinclude reducing signal noise from sensor signals and/or derivingindications of central tendency with techniques like averaging (simple,boxcar) or median filtering. More sophisticated filter types might alsoprove useful at this initial stage—given that each node contains a bevyof sensors, operation 1008 (or a later operation) may include performingsensor fusion algorithms like Kalman filtering or associated variants todetermine candidate events. A first node or sensor node 112 may forwardcandidate events to the sensor hub 116 to be processed with or comparedto other candidate events from other sensor nodes 112. Candidate eventsare events that are not necessarily directly observable by a sensor node112 (e.g., fire), but that are determined to exist when sensor data frommultiple sensors of a sensor node 112 are correlated. In this case, thesensor hub 116 may serve to increase the confidence level of a candidateevent from one sensor node 112 based on candidate events received fromother sensor nodes 112.

As described with reference to FIG. 2 , the method 1000 may include atleast one operation that triggers collection of sensor data by the firstnode 112 and/or by other first nodes 112 in the sensor system 118 byswitching the nodes 112 from an off-state or sleep state to an activestate for collecting sensor data.

Having the first node 112 perform the above-described operations of themethod 1000 corresponds to a first tier of processing that may improveperformance and/or efficiency of the sensor system 118.

Operation 1012 includes receiving, at a second node of the sensor system118, the first filtered dataset from the first node. The second node maycorrespond to the sensor hub 116. However, in the event that the sensorhub 116 is omitted or bypassed, the second node may correspond to theremote system 108. The second node 116 receives the first filtereddataset over a suitable wired and/or wireless connection as describedwith reference to FIGS. 3-6 .

Operation 1016 includes performing, at the second node 116, a second setof operations on the first filtered dataset to identify an eventexperienced by the structure envelope that caused the sensor to producethe first sensor data. As described above with reference to Table 1 andFIGS. 1-8 , the second set of operations includes consulting referencedata that associates events with rules (or rule sets) that should besatisfied for each event. The event is identified from the referencedata when the first filtered dataset satisfies at least one rule for theevent. Additionally or alternatively, the event is identified based onreferences values and/or ranges of reference values in the referencedata. For example, the sensor data from sensors of the first node ormultiple first nodes (sensor nodes 112) may indicate that the sensedparameters (e.g., impact, temperature, etc.) fall within rangesassociated with a particular event which is considered as the identifiedevent.

In at least one embodiment where the sensor system 118 includes multiplefirst nodes 112, operations 1012 and/or 1016 include receiving, at thesecond node 116 of the sensor system 118, a second filtered dataset froman additional first node 112 of the sensor system 118. The additionalfirst node 112 may also be in force-transmitting contact with the impactreceiving surface of the structure envelope. In this case, the secondset of operations includes identifying the event based on the firstfiltered dataset and the second filtered dataset. Identifying the eventbased on the first filtered dataset and the second filtered dataset mayinclude consulting the reference data in the same or similar manner asthat described above to evaluate the filter and second filtered datasetsagainst one or more rules, one or more reference values, or one orreference value ranges. An event is identified from the reference datawhen the first and second filtered datasets satisfy at least one ruleassociated with the identified the event.

As may be appreciated, the second filtered dataset is produced in thesame or similar manner as that described for the first filtered dataset.For example, the method 1000 includes steps that occur in parallel withoperations 1004 and/or 1008 where the additional first node 112 of thesensor system 118 produces second sensor data associated with thestructure envelope, and then filters out unwanted data in the secondsensor data to form the second filtered dataset in the same or similarmanner as filtered to arrive at the first filtered dataset. In at leastone example embodiment, the first sensor data and the second sensor dataare indicative of the same sensed parameters (e.g., impacts,temperature, etc.). Similarly, the first and second filtered datasetsare indicative of the same sensed parameters (e.g., impacts,temperature, etc.), but are reduced datasets compared to the first andsecond sensor data.

In one embodiment, operation 1016 includes the second node 116 focusingon inputs from multiple sensor nodes 112 for the purpose of increasingthe confidence in identifying events for reporting to the remote system108 and/or increasing the confidence in generating alerts that mayrequest or require some level of human action. If, for instance, despiteappropriate initial stage filtering at a first node 112, the first node112 reports impacts to the second node 116 that the first node 112identifies as hail but no other first nodes 112 in the structure 104have corroborating reports, then the second node 116 may conclude thatthe first node 112 reporting hail impacts has a sensor malfunction sincehail impacts are typically distributed across a roof and do not occur inone area. If such an anomalous event occurs more than a threshold numberof times, then the second node 116 may also generate a systemmaintenance alert that would prompt a service technician to check orreplace the sensor that has been producing untrustworthy data.

Operation 1020 includes sending, by the second node 116, the identifiedevent and associated data to a remote, third node of the sensor system118 such as the remote system 108 through a suitable wired and/orwireless connection (see FIGS. 3-6 , for example). Although notexplicitly shown, the second set operations and/or operation 1020 mayinclude steps to identify the associated data to send along with theidentified event to the third node 108. For example, certain subsets ofdata within the first and/or second filtered datasets received at thesecond node may be useful for sending along with the identified eventfor further processing at the third node 108 while other subsets of datawithin the first and/or second filtered datasets are not useful forfurther processing. Thus, the data in the first and/or second filtereddatasets that is not useful at the third node may be filtered out anddiscarded by the second node 116 (i.e., not sent to the third node 108).The third node 108 may provide the second node 116 with instructionsand/or information on which associated data to send with the identifiedevent and which sensor data to discard.

The associated data may comprise other information not associated withthe filtered datasets received from first nodes 112 by the second node116. For example, the associated data may include information about thestructure (e.g., structure age, roof age and type of materials used,structure size (total area), roof size (e.g., total area occupied byshingles), the structure's street address, owner contact informationand/or any other information that may be considered useful for thefurther processing at the third node. The associated data may includeinformation to identify other types of property owned by the propertyowner that are also insured by the insurance provider (e.g., vehicles).Such information may be useful since detection of an event like ahailstorm may also cause damage to the other types of property at thesame address. Inclusion of this information in the associated data mayprompt the property owner and/or the insurance provider to makerecommendations about the condition or claim status of the otherproperty types. In one embodiment, the third node 108 has access to astorage device that pre-stores such information or other informationassociated with the structure and/or identified events so that thesecond node 116 can include pointers to the stored information stored atthe third node 108 instead of the information itself.

As may be appreciated, having the second node 116 identify the event anddetermine which sensor data to send with the identified event to thethird node 108 corresponds to a second tier of processing that mayimprove performance and/or efficiency of the sensor system 118. Thesecond tier of processing may be more complex than the first tier ofprocessing carried out by first nodes 112.

Operation 1024 includes performing, at the third node 108, furtherprocessing on the identified event and the associated data. The furtherprocessing includes operations that an interested entity (homeowner,insurance company, etc.) finds useful for assessing a condition of thestructure, for drawing conclusions about the condition of the structure,and/or for making recommendations to the interested entity (e.g., seekrepair, schedule inspections, take no action, etc.). In one embodiment,performing the further processing includes determining a condition ofthe structure based on the identified event and the associated data, andthen generating a notification to notify an interested entity of thecondition of the structure. Here, the notification may comprise arecommendation have an inspector conduct a manual inspection of thestructure. The recommendation may be made to one or more interestedentities, such as the property owner and the home insurance provider. Asnoted above, the further processing may include using the identifiedevent and associated data as training data for a machine learningalgorithm and/or a neural network design to improve detection of eventsand responses of interested parties to detected events.

In one non-limiting example, the further processing includes the thirdnode 108 identifying an event, for example, if the second node 116passes sensor data and/or other data to the third node 108 without anidentified event or with a partially identified event. Identifying anevent at the third node 108 may occur to confirm the event identified atthe second node or when the second node 116 is unable to identify theevent as a result of a lack of reference data or the lack of processingcapability. In the scenario where the second node 116 is unable toidentify an event as a result of being unable to match filtered datasets to corresponding reference data that belongs to an event, the thirdnode 108 may have a more complete set of reference data as a result ofhaving immediate access to information from multiple structures 104.Indeed, the remote system 108 serves many structures 104 and analyzesdata received from these structures to, among other things, hone eventidentification and/or to create new events.

For example, one or more sensor nodes 112 may detect abnormal airparticulate levels as a result of smoke in an attic where the sensornodes 112 are mounted, but the second node 116 cannot identify aparticular event. In this case, the data regarding detected particulatelevels may be passed to the third node 108 where the third node 108 isable to identify a “smoke detected” event using a more complete set ofreference data gleaned from data received from other structures 104. Thesecond node 116 may not be able to identify an event for multiplereasons including but not limited to the second node 116 not having thecapability (e.g., due to a malfunction or due to design), the secondnode 116 not having an updated set of reference data that accounts forparticulate levels, the detected particulate levels not being sufficientfor the second node 116 identify the event with the current set ofreference data that does account for particular levels, and/or the like.

Operation 1028 includes accessing, in response to generating thenotification, a calendar of the inspector while operation 1032 includesplacing an entry in the calendar for the inspector to conduct the manualinspection and/or notifying the property owner of the time and date ofinspection. Operations 1028 and 1032 may occur automatically at thethird node 108 without or with little human intervention so that burdenon the property owner and/or the insurance provider is reduced after theoccurrence of an event, which may further improve the efficiencyhandling insurance claims related to the event. Operations 1028 and 1032may be optional operations for the method 1000. Other post-processingtype operations may be carried out as part of the method 1000 dependingon the scenario. For example, the third node 108 may associate detectedmovement of the structure 104 as exceeding a threshold amount andidentify an earthquake event, which may prompt inspection scheduling, ora recommendation to condemn the structure 104 if the movement exceeds alarger threshold amount. In yet another example, the temperature acrossthe sensor nodes 112 may vary by more than a threshold amount, which cantrigger a recommendation to inspect the insulation in locations wherethe temperature variation is over the threshold amount.

The method 1000 has been described with reference to two sensor nodes112 (e.g., the first node and the additional first node) that providefiltered datasets to a second node such as the sensor hub 116. However,additional filtered datasets may be received by the second node 116 fromas many sensor nodes 112 that are at the structure 104 so that themethod 1000 takes all of this data into account.

In view of the above, it should be appreciated that at least one exampleembodiment is directed to a sensor system 118 for a structure 104. Thesensor system 118 may comprise a sensor node 112 in force transmittingcontact with an impact receiving surface of a structure envelope of thestructure 104. The sensor node 112 is configured to generate firstsensor data associated with the structure envelope of the structure, andperform a first set of operations to filter out unwanted data from thefirst sensor data to form a first filtered dataset. The sensor system118 may further comprise a sensor hub 116 in communication with thesensor node 112. The sensor hub 116 is configured to receive the firstfiltered dataset from the sensor node, and perform a second set ofoperations on the first filtered dataset to identify an eventexperienced by the structure envelope that caused the sensor node toproduce the first sensor data. The sensor system 118 may further includeor be in communication with a remote system 108. The sensor hub 116 maysend the identified event and associated data to the remote system.Here, the remote system 108 is configured to perform further processingon the identified event and the associated data.

In view of the instant description, example embodiments propose to solvetechnical problems that plague property owners and/or the propertyinsurance industry. Such technical problems include inefficienciesrelated to damage assessment, delayed reporting of incidents, fraudulentreporting of incidents, and/or unnecessary reporting of incidents.Additional technical problems include inefficiencies in determining thecondition of a structure after an event for the purposes of schedulingan inspection, estimating likely repairs and associated costs, and/orthe like. Another technical problem arises in that an interested entitymay be overloaded with sensor data related to the occurrence of anevent. Example embodiments propose to solve these and other technicalproblems not explicitly stated herein with a sensor system that providesmultiple tiers of processing to filter out unwanted sensor data prior toadditional (sometimes more involved) processing steps that occur at aremote system located offsite from the structure while providing timelyand accurate event detection and associated information to interestedparties. The sensor nodes perform a first tier of processing to filtersensor data passed to the sensor hub, the sensor hub performs a secondtier of processing to filter data passed to the remote system, and theremote system performs backend processing with a wholistic view of datafrom multiple structures. Each tier of processing may increase incomplexity (from the sensor nodes, to the sensor hub, to the remotesystem) so that the sensor system provides a cost-effective and accurateway to handle the interaction between property owners and insuranceproviders.

Specific details were given in the description to provide a thoroughunderstanding of the embodiments. However, it will be understood by oneof ordinary skill in the art that the embodiments may be practicedwithout these specific details. In other instances, well-known circuits,processes, algorithms, structures, and techniques may be shown withoutunnecessary detail in order to avoid obscuring the embodiments.

While illustrative embodiments of the disclosure have been described indetail herein, it is to be understood that the inventive concepts may beotherwise variously embodied and employed, and that the appended claimsare intended to be construed to include such variations, except aslimited by the prior art.

It should be appreciated that inventive concepts cover any embodiment incombination with any one or more other embodiment, any one or more ofthe features disclosed herein, any one or more of the features assubstantially disclosed herein, any one or more of the features assubstantially disclosed herein in combination with any one or more otherfeatures as substantially disclosed herein, any one of theaspects/features/embodiments in combination with any one or more otheraspects/features/embodiments, use of any one or more of the embodimentsor features as disclosed herein. It is to be appreciated that anyfeature described herein can be claimed in combination with any otherfeature(s) as described herein, regardless of whether the features comefrom the same described embodiment. Embodiments may be configured asfollows:

(1) A sensor system for a structure, the sensor system comprising:

a sensor node in force transmitting contact with an impact receivingsurface of a structure envelope of the structure, the sensor node beingconfigured to:

-   -   generate first sensor data associated with the structure        envelope of the structure; and    -   perform a first set of operations to filter out unwanted data        from the first sensor data to form a first filtered dataset;

a sensor hub in communication with the sensor node, the sensor hub beingconfigured to:

-   -   receive the first filtered dataset from the sensor node; and    -   perform a second set of operations on the first filtered dataset        to identify an event experienced by the structure envelope that        caused the sensor node to produce the first sensor data.        (2) The sensor system of (1), further comprising:

an additional sensor node in force transmitting contact with the impactreceiving surface of the structure envelope, wherein the sensor hub isconfigured to:

-   -   receive a second filtered dataset from the additional sensor        node, wherein the second set of operations includes:        -   identifying the event based on the first filtered dataset            and the second filtered dataset.            (3) The sensor system of one or more of (1) to (2), wherein            identifying the event based on the first filtered dataset            and the second filtered dataset includes:

consulting reference data that associates events with reference valuesfor the first and second filtered datasets.

(4) The sensor system of one or more of (1) to (3), wherein identifyingthe event based on the first filtered dataset and the second filtereddataset includes:

consulting reference data that associates events with rules that shouldbe satisfied for each event.

(5) The sensor system of one or more of (1) to (4), wherein the event isidentified from the reference data when the first and second filtereddatasets satisfy at least one rule for the event.

(6) The sensor system of one or more of (1) to (5), wherein theadditional sensor node is configured to:

produce second sensor data associated with the structure envelope; and

filter out unwanted data in the second sensor data to form the secondfiltered dataset.

(7) The sensor system of one or more of (1) to (6), wherein the firstset of operations includes:

comparing the first sensor data to one or more thresholds; and

identifying data in the first sensor data as unwanted data or as data ofthe first filtered dataset based on the comparison.

(8) The sensor system of one or more of (1) to (7), wherein the unwanteddata corresponds to data that is not relevant to identifying an event,and wherein the first filtered dataset corresponds to data that isrelevant to identifying an event.

(9) The sensor system of one or more of (1) to (8), wherein the secondset of operations includes:

consulting reference data that associates events with rules that shouldbe satisfied for each event, wherein the event is identified from thereference data when the first filtered dataset satisfies at least onerule for the event.

(10) The sensor system of one or more of (1) to (9), further comprising:

a remote system, wherein the sensor hub is configured to:

-   -   send the identified event and associated data to the remote        system, wherein the remote system is configured to perform        further processing on the identified event and the associated        data.        (11) The sensor system of one or more of (1) to (10), wherein        the further processing includes:

determining a condition of the structure based on the identified eventand the associated data; and

generating a notification to notify an interested entity of thecondition of the structure.

(12) The sensor system of one or more of (1) to (11), wherein thenotification comprises a recommendation have an inspector conduct amanual inspection of the structure.

(13) The sensor system of one or more of (1) to (12), wherein the remotesystem is configured to:

access, in response to generating the notification, a calendar of theinspector; and

place an entry in the calendar for the inspector to conduct the manualinspection.

(14) The sensor system of one or more of (1) to (13), wherein the sensorcomprises an impact sensor so that the first sensor data is indicativeof impacts to the impact receiving surface of the structure envelope.

(15) An impact detection method for a structure, the method comprising:

producing, by an impact sensor of a first node of a sensor system, firstsensor data associated with a structure envelope of the structure, theimpact sensor being in force-transmitting contact with an impactreceiving surface of the structure envelope to detect impacts to theimpact receiving surface;

performing, at the first node, a first set of operations to filter outunwanted data from the first sensor data to form a first filtereddataset;

receiving, at a second node of the sensor system, the first filtereddataset from the first node; and

performing, at the second node, a second set of operations on the firstfiltered dataset to identify an event experienced by the structureenvelope that caused the sensor to produce the first sensor data.

(16) The method of (15), further comprising:

receiving, at the second node of the sensor system, a second filtereddataset from an additional first node of the sensor system, wherein thesecond set of operations includes:

-   -   identifying the event based on the first filtered dataset and        the second filtered dataset.        (17) The method of one or more of (15) to (16), wherein        identifying the event based on the first filtered dataset and        the second filtered dataset includes:

consulting reference data that associates events with rules that shouldbe satisfied for each event.

(18) The method of one or more of (15) to (17), further comprising:

sending, by the second node, the identified event and associated data toa remote, third node of the sensor system;

performing, at the third node, further processing on the identifiedevent and the sensor data.

(19) The method of one or more of (15) to (18), wherein the furtherprocessing includes:

determining a condition of the structure based on the identified eventand the associated data; and

generating a notification to notify an entity of the condition of thestructure, the entity being associated with the third node of the sensorsystem.

(20) A sensor system, comprising:

a first node in force transmitting contact with an impact receivingsurface of a structure envelope of the structure, the first node beingconfigured to:

-   -   generate first sensor data associated with the structure        envelope of the structure;    -   perform a first set of operations to filter out unwanted data        from the first sensor data to form a first filtered dataset;

a second node in communication with the first node, the second nodebeing configured to:

-   -   receive the first filtered dataset from the first node; and    -   perform a second set of operations on the first filtered dataset        to identify an event experienced by the structure envelope that        caused the first node to produce the first sensor data.

What is claimed is:
 1. A sensor system for a structure, the sensorsystem comprising: a sensor node including a plurality of sensors housedin a single housing, the plurality of sensors including: at least onesensor that senses one or more aspects of an environment within orsurrounding the sensor node; and a first impact sensor in forcetransmitting contact with an impact receiving surface of a roof of thestructure, the sensor node being configured to: generate, from theplurality of sensors, first sensor data associated with the roof of thestructure; and perform a first set of operations to filter out unwanteddata from the first sensor data to form a first filtered datasetincluding sensor data from the first impact sensor and the at least onesensor; a sensor hub in communication with the sensor node, the sensorhub being configured to: receive the first filtered dataset from thesensor node; and perform a second set of operations on the firstfiltered dataset to identify an event experienced by the roof thatcaused the sensor node to produce the first sensor data; and a remotesystem located remotely from the sensor hub, wherein the sensor hub isconfigured to send the identified event and associated data to theremote system, wherein the remote system is configured to performfurther processing on the identified event and the associated data,wherein the associated data includes a timestamp of when the identifiedevent occurred, and wherein the further processing by the remote systemincludes: determining a time window that encompasses the timestamp, alength of the time window being determined based on first informationindicating how long the identified event lasted; identifying an area ofinterest based on second information indicating a location of theidentified event, the area of interest including one or more otherstructures that experienced the identified event; analyzing other datacollected during the time window by sensor nodes of the one or moreother structures in the area of interest; and confirming ordisconfirming the occurrence of the identified event as identified bythe sensor hub based on the analysis of the other data.
 2. The sensorsystem of claim 1, further comprising: an additional sensor node inforce transmitting contact with the impact receiving surface of theroof, wherein the sensor hub is configured to: receive a second filtereddataset from the additional sensor node, wherein the second set ofoperations includes: identifying the event based on the first filtereddataset and the second filtered dataset, wherein the unwanted datafiltered out from the first sensor data includes unwanted sensor datafrom the first impact sensor and unwanted sensor data from the at leastone sensor that senses one or more aspects of the environment, andwherein the plurality of sensors further comprises a temperature sensor,an acoustic sensor, and a humidity sensor.
 3. The sensor system of claim2, wherein identifying the event based on the first filtered dataset andthe second filtered dataset includes: consulting reference data thatassociates events with reference values for the first and secondfiltered datasets.
 4. The sensor system of claim 2, wherein identifyingthe event based on the first filtered dataset and the second filtereddataset includes: consulting reference data that associates events withrules that should be satisfied for each identified event.
 5. The sensorsystem of claim 4, wherein the identified event is identified from thereference data when the first and second filtered datasets satisfy atleast one of the rules.
 6. The sensor system of claim 2, wherein theadditional sensor node includes a second impact sensor and at least onesensor that senses one or more aspects of an environment within orsurrounding the additional sensor node, and wherein the additionalsensor node is configured to: produce second sensor data from the secondimpact sensor and the at least one sensor of the additional sensor node;and filter out unwanted data in the second sensor data to form thesecond filtered dataset.
 7. The sensor system of claim 1, wherein thefirst information and the second information are retrieved from a sourceexternal to the sensor node and the sensor hub, wherein output of one ofthe plurality of sensors wakes up the sensor node from a low power stateto cause the sensor node to initiate the first set of operations, andwherein the first set of operations includes: comparing the first sensordata to one or more thresholds; and identifying data in the first sensordata as the unwanted data or as data of the first filtered dataset basedon the comparison.
 8. The sensor system of claim 7, wherein the housingcomprises a flat surface that mounts to an underside of the roof,wherein the unwanted data corresponds to data that is not relevant toidentifying an event, and wherein the first filtered dataset correspondsto data that is relevant to identifying an event.
 9. The sensor systemof claim 1, wherein the second set of operations includes: consulting atable that includes a list of possible events, wherein, for eachpossible event, the table lists a subset of sensors in the plurality ofsensors and a range of values for each parameter sensed by the subset ofsensors, wherein the sensor hub selects a possible event from the listas the identified event when all parameters sensed by the subset ofsensors for the selected possible event fall within corresponding rangesof values, and wherein the subset of sensors differs for at least someof the possible events.
 10. The sensor system of claim 1, wherein thesensor node identifies a candidate event using the first filtereddataset and sends the candidate event to the sensor hub, wherein thecandidate event is not directly observable from individual outputs ofthe plurality of sensors, and wherein the sensor hub adjusts aconfidence level of the candidate event based on at least one additionalcandidate event received by the sensor hub from an additional sensornode.
 11. The sensor system of claim 1, wherein the further processingincludes: determining a condition of the structure based on theidentified event and the associated data; and generating a notificationto notify an interested entity of the condition of the structure. 12.The sensor system of claim 11, wherein the notification comprises arecommendation have an inspector conduct a manual inspection of thestructure.
 13. The sensor system of claim 12, wherein the remote systemis configured to: access, in response to generating the notification, acalendar of the inspector; and place an entry in the calendar for theinspector to conduct the manual inspection.
 14. The sensor system ofclaim 1, further comprising: a sensor calibrator included in the sensornode or the sensor hub and that outputs vibrations detectable by thefirst impact sensor to calibrate the first impact sensor or to perform afunctional check of the first impact sensor.
 15. An impact detectionmethod for a structure, the method comprising: producing, by an impactsensor and at least one sensor of a first node of a sensor system, firstsensor data associated with a roof of the structure, the impact sensorbeing in force-transmitting contact with an impact receiving surface ofthe roof to detect impacts to the impact receiving surface, wherein theat least one sensor senses one or more aspects of an environment withinor surrounding the first node, and wherein the impact sensor and the atleast one sensor are included with a plurality of sensors housed in asame housing; performing, at the first node, a first set of operationsto filter out unwanted data from the first sensor data to form a firstfiltered dataset including sensor data from the impact sensor and the atleast one sensor; receiving, at a second node of the sensor system, thefirst filtered dataset from the first node; and performing, at thesecond node, a second set of operations on the first filtered dataset toidentify an event experienced by the roof that caused the impact sensorand the at least one sensor to produce the first sensor data, whereinthe second set of operations includes consulting a table that includes alist of possible events, wherein, for each possible event, the tablelists a subset of sensors in the plurality of sensors and a range ofvalues for each parameter sensed by the subset of sensors, wherein thesecond node selects a possible event from the list as the identifiedevent when all parameters sensed by the subset of sensors for theselected possible event fall within corresponding ranges of values, andwherein the subset of sensors differs for at least some of the possibleevents.
 16. The method of claim 15, further comprising: receiving, atthe second node of the sensor system, a second filtered dataset from anadditional first node of the sensor system, wherein the second set ofoperations includes: identifying the event based on the first filtereddataset and the second filtered dataset.
 17. The method of claim 16,wherein identifying the event based on the first filtered dataset andthe second filtered dataset includes: consulting reference data thatassociates events with rules that should be satisfied for each event.18. The method of claim 16, further comprising: sending, by the secondnode, the identified event and associated data to a remote, third nodeof the sensor system; and performing, at the third node, furtherprocessing on the identified event and the associated data, wherein theassociated data includes a timestamp of when the identified eventoccurred, and wherein the further processing includes: determining atime window that encompasses the timestamp, a length of the time windowbeing determined based on first information indicating how long theidentified event lasted; identifying an area of interest based on secondinformation indicating a location of the identified event, the area ofinterest including one or more other structures that experienced theidentified event, analyzing other data collected during the time windowby sensor nodes of the one or more other structures in the area ofinterest; and confirming or disconfirming the occurrence of theidentified event as identified by the second node based on the analysisof the other data.
 19. The method of claim 18, wherein the furtherprocessing includes: determining a condition of the structure based onthe identified event and the associated data; and generating anotification to notify an entity of the condition of the structure, theentity being associated with the third node of the sensor system.
 20. Asensor system, comprising: a first node in force transmitting contactwith an impact receiving surface of a roof of a structure, the firstnode including a plurality of sensors, the plurality of sensorsincluding an impact sensor and at least one sensor housed in a singlehousing, the at least one sensor sensing one or more aspects of anenvironment within or surrounding the first node, the first node beingconfigured to: generate, from the plurality of sensors, first sensordata associated with the roof of the structure; and correlate the firstsensor data to identify a first candidate event that caused theplurality of sensors to generate the first sensor data, wherein thefirst candidate event is not directly identifiable from individualoutputs of the plurality of sensors; and a second node in communicationwith the first node, the second node being configured to: receive thefirst candidate event from the first node; receive second candidateevents from other first nodes of the sensor system, wherein the secondcandidate events are not directly identifiable from individual outputsof sensors of the other first nodes; and adjust a confidence level ofthe first candidate event based on the second candidate events.